There are numerous applications in the video processing arts where it is necessary to either track objects of interest from one image frame to the next, or to record an image and compare the saved image with another saved image or a current image. In general, such applications include unmanned air vehicle (UAV) navigation, mapping, object identification, and scene reconstruction.
For example, when identifying an object on the ground from a camera on a UAV, the system tracks the object from image frame to image frame until a level of certainty is reached that the object is identified. Objects are identified by passing the information from each successive image frame to a classification algorithm. In identifying the object of interest from image frame to image frame, each image frame or a portion thereof must be processed and reprocessed until the associated classification algorithm's output level has exceeded a predetermined threshold at which point an identification is declared. Such processing and reprocessing requires a tremendous amount of computer resources.
Consequently, video correlation tracking would benefit from an improved system that tracks objects and registers images with a minimal expenditure of processing time and other